Backend Data Engineer IntraEdge Technology

5.0 - 10.0 years

15 - 30 Lacs

Chennai

Hybrid

Job Summary: We are looking for a highly skilled Backend Data Engineer to join our growing FinTech team. In this role, you will design and implement robust data models and architectures, build scalable data ingestion pipelines, and ensure data quality across financial datasets. You will play a key role in enabling data-driven decision-making by developing efficient and secure data infrastructure tailored to the fast-paced FinTech environment. Key Responsibilities: Design and implement scalable data models and data architecture to support financial analytics, risk modeling, and regulatory reporting. Build and maintain data ingestion pipelines using Python or Java to process high-volume, high-velocity financial data from diverse sources. Lead data migration efforts from legacy systems to modern cloud-based platforms. Develop and enforce data validation processes to ensure accuracy, consistency, and compliance with financial regulations. Create and manage task schedulers to automate data workflows and ensure timely data availability. Collaborate with product, engineering, and data science teams to deliver reliable and secure data solutions. Optimize data processing for performance, scalability, and cost-efficiency in a cloud environment. Required Skills & Qualifications: Proficiency in Python and/or Java for backend data engineering tasks. Strong experience in data modelling , ETL/ELT pipeline development , and data architecture . Hands-on experience with data migration and transformation in financial systems. Familiarity with task scheduling tools (e.g., Apache Airflow, Cron, Luigi). Solid understanding of SQL and experience with relational and NoSQL databases. Knowledge of data validation frameworks and best practices in financial data quality. Experience with cloud platforms (AWS, GCP, or Azure), especially in data services. Understanding of data security , compliance , and regulatory requirements in FinTech. Preferred Qualifications: Experience with big data technologies (e.g., Spark, Kafka, Hadoop). Familiarity with CI/CD pipelines , containerization (Docker), and orchestration (Kubernetes). Exposure to financial data standards (e.g., FIX, ISO 20022) and regulatory frameworks (e.g., GDPR, PCI-DSS). Role & responsibilities Preferred candidate profile

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